<i>Euclid</i>: Early Release Observations – NISP-only sources and the search for luminous <i>z</i> = 6–8 galaxies
Bibliographic record
Abstract
This paper presents a search for high redshift galaxies from the iEuclid/i Early Release Observations program ‘Magnifying Lens.’ The 1.5 degsup2/sup area covered by the twin Abell lensing cluster fields is comparable in size to the few other deep near-infrared surveys such as COSMOS, and so provides an opportunity to significantly increase known samples of rare UV-bright galaxies at iz/i ≈ 6–8 (iM/isubUV/sub ≲ −22). Beyond their still uncertain role in reionisation, these UV-bright galaxies are ideal laboratories from which to study galaxy formation and constrain the bright-end of the UV luminosity function. Of the 501 994 sources detected from a combined iY/isubE/sub, iJ/isubE/sub, and iH/isub/subE NISP detection image, 168 do not have any appreciable VIS/iI/isubE/sub flux. These objects span a range in spectral colours, separated into two classes: 139 extremely red sources; and 29 Lyman-break galaxy candidates. Best-fit redshifts and spectral templates suggest the former is composed of both iz/i ≳ 5 dusty star-forming galaxies and iz/i ≈ 1–3 quiescent systems. The latter is composed of more homogeneous Lyman-break galaxies at iz/i ≈ 6–8. In both cases, contamination by L- and T-type dwarfs cannot be ruled out with iEuclid/i images alone. Additional contamination from instrumental persistence is investigated using a novel time series analysis. This work lays the foundation for future searches within the Euclid Deep Fields, where thousands more iz/i ≳ 6 Lyman-break systems and extremely red sources will be identified.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".